Kedis ku xidhan hagaha · Dhexdhexaad Heerka

T5 iyo Kediska Gudbinta Qoraal-u-Qoraalka

Tijaabi horgalayaasha hawsha T5, musuqmaasuqa baaxadda leh, feejignaanta cod-dejiyaha, iyo faraqa u dhexeeya habaynta tilmaanta iyo jawaabaha buug-xidhan.

Wadooyinka haga ee la xidhiidhaT5 Iyo Qoraalka Gudbinta Qoraalka
Su'aal 1 ee 8

Waa maxay fikradda qeexan ee ka dambeysa T5?

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  1. Waa maxay fikradda qeexan ee ka dambeysa T5?
    • Waxa kaliya oo ay qabato turjumaada mashiinka
    • Waxay ka abuurtaa sawirro qoraallo
    • Hawl kasta oo NLP ah waxaa loo qaabeeyey sidii gelinta qoraalka ee soo saarista qoraalka
    • Waxay ku beddeshaa dhammaan tababbarka barashada xoojinta
  2. Waa maxay qaab-dhismeedka Transformer T5 uu isticmaalo?
    • Codeeye buuxa
    • Encoder-kaliya, sida BERT
    • Decoder-kaliya, sida GPT
    • Wax dareen ah haba yaraatee
  3. Waa maxay hadafka hore ee tababarka uu T5 ugu horrayn isticmaalo?
    • Saadaasha jumlada xigta kaliya
    • Saadaasha qiimaha saamiyada
    • Sawirka rinjiyeynta
    • Musuqmaasuqa baaxadda leh, qarinta taako isku xigta oo lagu beddelay calaamado sentinel
  4. Korpuskee T5 horay loogu tababaray?
    • Kaliya Wikipedia
    • C4 Colossal Nadiif ah oo gurguurantay Corpus
    • Xogta koodhka isha
    • Qoraallada maqalka ah
  5. Sidee T5 u matalaysaa hawsha kala soocida sida falanqaynta dareenka?
    • Waxay soo saartaa vector ixtimaalka kaliya
    • Waxay soo celinaysaa aqoonsiga lambar
    • Waxay abuurtaa erayga summada dhabta ah, sida 'positive' ama 'negative'
    • Ma samayn karto kala saarid
  6. Waa maxay FLAN-T5 marka loo eego T5 asalka ah?
    • Qaab sawir yar
    • Farcan edbin habaysan oo soo koobaya hawlaha aan la arkin
    • Habka aqoonsiga hadalka
    • Qalabka xogta ee aan xidhiidh la lahayn
  7. When T5 generates a summary, what does decoder cross-attention let it consult?
    • The encoder's representations of the input article
    • Only previously generated summary tokens
    • Only the unprocessed task label
    • The training optimizer's stored gradients
  8. In a closed-book T5 question-answering setup, where does the answer's factual information come from at inference?
    • A document retrieval step required for every question
    • A newly supplied answer passage required in the prompt
    • A live database lookup built into span corruption
    • Knowledge encoded in the model's learned parameters